Automated merge - qualcomm/Startup-Demos:feature_rel_20260506_114149 -> qualcomm/Startup-Demos:main#178
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smartcoder00 merged 3 commits intomainfrom May 6, 2026
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- The Industrial Anomaly Detection application demonstrates real-time AI-powered detection of industrial hazards (fire and leakage) using the Arduino UNO Q board integrated with a USB webcam and Edge Impulse machine learning models . - The system provides immediate visual feedback through both a web-based interface displaying live video with detection labels and an LED matrix that shows distinct patterns for each anomaly type . Signed-off-by: Shashank Chikkanayakanahalli Vishwaradhya (Shashank C V) (Temp) <shascv@qti.qualcomm.com>
- The Industrial Anomaly Detection application demonstrates real-time AI-powered detection of industrial hazards (fire and leakage) using the Arduino UNO Q board integrated with a USB webcam and Edge Impulse machine learning models . - The system provides immediate visual feedback through both a web-based interface displaying live video with detection labels and an LED matrix that shows distinct patterns for each anomaly type .
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Approved the changes after reviewing all the below checklists.
𝗖𝗢𝗠𝗠𝗜𝗧𝗦 & 𝗣𝗥 𝗛𝗬𝗚𝗜𝗘𝗡𝗘
- Clear PR title & brief description
- Commit messages follow standards
- All commits are signed
- Project Information file should meet the standards
- CI / QC Preflight checks green
𝗖𝗢𝗗𝗘 𝗤𝗨𝗔𝗟𝗜𝗧𝗬 & 𝗔𝗨𝗧𝗛𝗘𝗡𝗧𝗜𝗖𝗜𝗧𝗬 - No copied code without proper source/license
- Ask author for source of suspicious lines
- No ML models / datasets / binaries checked in
- Code belongs in source files (not in README)
𝗗𝗢𝗖𝗨𝗠𝗘𝗡𝗧𝗔𝗧𝗜𝗢𝗡 𝗗𝗜𝗦𝗖𝗜𝗣𝗟𝗜𝗡𝗘 - README simple, clean, minimal
- No long code blocks in README
- Reusable docs moved to common README/docs
- Clear git clone + setup instructions
- Use scripts for repeatable setup
𝗖𝗢𝗠𝗣𝗟𝗜𝗔𝗡𝗖𝗘 & 𝗦𝗔𝗙𝗘𝗧𝗬 - Dependencies & licenses validated
- No secrets or sensitive data
- No copyrighted media included
- All reviewer comments resolved before merge
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Automated merge via script.